Introduction and my own tracks

Reasearch introduction

Dear reader,

My name is Sven and this is the dashboard I have made in the course Computational Musicology.

In this dashboard, I will show different visualisation based on several tracks made by our class. First, I will introduce our class corpus with a few graphs and show different Essentia-features in relation to the tracks. Second, I will analyse six songs based on their structure, tonal features and tempo. Third, I will build a model for predicting danceability in the class corpus. At the final page, I will end this dashboard by a concluding section.

This dashboard will be guided by the following question: what musical features contribute to danceability within our class corpus?

Own tracks in compmus2025

Let me start off by telling some more about my own tracks.

AI Prompts: For the first track, I used https://www.jenmusic.ai to create it and provided it with the following prompt: “I would like a 6/8 meter, often stressing this meter, but at certain moments provided with hemiolas. It should be a ballad, structured as: intro - verse - pre-chorus - chorus - break - verse - chorus - chorus - outro. As instruments, it should use a piano, soft percussion, a string quartet and some woodwinds. The piano provides a progression consisting of chords with additional notes (such as 7ths, 9ths, 11ths, 13ths) and sus-chords. The soft percussion starts minimal, but gets more extensive in the choruses. The strings play throughout the whole song, but the viola mainly provides the melody. The woodwinds are only used to emphasize the pre-chorus and the chorus. The ballad should be in D major as key and has a slow to medium tempo. The reverb should be as if the piece is played in a small hall.” I tried to be specific in many aspects to see if the AI tool would create something that would meet my ‘demands’. Even though it did not in many ways, it picked up on some features of the prompt.

For the second track, I used https://www.stableaudio.com to create it and provided it with the following prompt: “soft ballad, 6/8, D major, slow to medium tempo, piano, soft percussion gets more extensive over-time, string quartet, melody played by viola, soft woodwinds, triad chords played by piano, added note chords played by piano, hemiolas, small hall reverb.” This tool specified that it would work better when using short descriptions, so I tried to recreate the prompt I used for track one as much as I could with this in mind. Some ‘demands’ are now less elaborate or not mentioned at all. Again, it does seem to leave out some ‘demands’, but many others are to some extent met.

Class Corpus Table

Column 1

Compmus2025 Table

This table shows a diverse range of information about the tracks. Besides the filenames, it displayes the approachability, arousal, danceability, engagingness, instrumentalness, tempo, valence, usage of ai to create the track and the names_tracknumber of the students.The information in this table will be the base for my first visualisation. In order to create the dance column, I used the condition that danceability >= 0.7 for a track to be danceable (= true). Every track that has a danceability < 0.7 is then non-danceable (= false).

First Class Corpus Visualisations

Comparison of all songs

This graph shows the relationship between the danceability and arousal. Especially at the beginning of the graph, it seems like there is a correlation: when danceability rises, so does arousal. Combining this with engagingness, which is shown by the size of the dots, it can be seen that when danceability and arousal rise, there is often also an increase in engagingness.

Lastly valence is added to the graph as the colour of the dots. It can be seen that often valence and engagingness increase together. However, at certain moments, the relationship between valence and engagingness is less apparent.

Whose song is the most danceable?

In this graph, I show the daneability of each track in the class corpus in relation to the others: the higher the bar, the higher the danceability. The colors of the bars corresponds to the question whether AI has been used to create to track.

Songs I will use in this dashboard

The tracks displayed in this graph will be compared throughout my dashboard. Besides my own two tracks, I choose the two most and the two least danceable tracks. As shown, my own tracks are on the low side of the danceability spectrum as well.

Marit_1

Chromagram and Cepstrogram

Chromagram

Cepstrogram

Self-similarity Matrices

Chroma-based Matrix

Timbre-based Matrix

Comments

The combination of the Chroma-based SSM and the Timbre-based SSM shows a clear structure in the song. The Chroma-based SSM shows that there is a repeating riff throughout most of the song by the many small recurring patterns and the many dark diagonal lines. The Timbre-based SSM shows a few parts that are slightly different from other parts. The structure could be seen as Intro-A1-B-A2-Outro.

Based on both SSMs:

On 0:00 a guitar riff starts playing, the repetition of it can be seen in the Chroma-based SSM.
On 0:15 high-hats and a synthesizer are added, which shows a change in the Timbre-based SSM.
On 0:30 a kick and snare are added.
On 1:18 the drums change their rhythm and there is some more distortion, which can be seen by the cross in both the SSMs.
On 1:43 clear harmonies are added (a bass?), which ends the cross-section in the Timbre-based SSM.
On 2:45 most of the instruments fade away and there is only a guitar riff left, shown in the Timbre-based SSM.

All these moments are shown by changes in the SSMs.

Ke_2

Chromagram and Cepstrogram

Chromagram

Cepstrogram

Self-similarity Matrices

Chroma-based Matrix

Timbre-based Matrix

Comments

The Chroma-based SSM and the Timbre-based SSM show the same structure. There are two section constantly alternating and an additional bridge. The track is structured as A-B1-A-B2-A-C-A-Outro.

B1 and B2 are almost the same, except for the addition of a vocal-humming in B2. This second B section is also double the length of B1 and the small addition happens in the second half. The Outro part uses the same material as A, but adds a low-pass filter on it in the second half.

Sven_2

Chromagram and Cepstrogram

Chromagram

Cepstrogram

Self-similarity Matrices

Chroma-based Matrix

Timbre-based Matrix

Comments

The Chroma-based SSM shows a clear structure in the song. In combination with the Timbre-based SSM, the structure could be seen as: A1-B-C-A2.

I will combine both of the SSMs to analyse the structure, but mainly base myself on the Timbre-based SSM:

On 0:00 a piano melody starts playing.
On 0:17 high-hats and strings are added.
On 0:30 a different piano melody starts playing.
On 0:49 a string instrument gets more prominence. The Chroma-based SSM also clearly shows this by the different texture starting at this moment.
On 1:20 another string instrument starts playing.
On 1:43 the high-hats are reintroduced and play over a piano melody accompanied by strings. This is a new section as is shown by the Chroma-based SSM.
On 2:35 a new piano melody is played over the high-hats and soft strings. It sound familiar, like it is a varied form of the first melody.

All these moments are shown by changes in the SSM. Even though there are more changes visible than I can hear in the music, it does a well job in showing the structure of the music.

Sven_1

Chromagram and Cepstrogram

Chromagram

Cepstrogram

Self-similarity Matrices

Chroma-based Matrix

Timbre-based Matrix

Comments

Both the Chroma-based SSM as the Timbre-based SSM do not show a very clear structure. There seem to be a lot of changes throughout the track, without a very stable structure. The structure could be seen as a A1-B-A2-C, but it is not really convincing.

The Timbre-based SSM is somewhat clearer:

On 0:00 a combination of strings, woodwinds and percussion starts playing.
On 0:06 a more steady drum patterns gets introduced.
On 0:55 most instruments suddenly stop playing. A short drum and string pattern plays, where after the music continues with the same instruments as before, but a different melody and different drum pattern.
On 1:47 a short string part introduces another new melody and drum pattern.
On 2:30 a short flute solo starts accompanied by the other instruments.

All these moments are shown by changes in the SSMs. Even though there are more changes visible than I can hear in the music, it does a well job in showing the music’s structure.

Roemer_1

Chromagram and Cepstrogram

Chromagram

Cepstrogram

Self-similarity Matrices

Chroma-based Matrix

Timbre-based Matrix

Comments

The Chroma-based SSM does not shows a very clear structure in the song. However, by the small diagonal lines, it shows that from around 55 seconds towards the ending many repetition of the material takes place.

The Timbre-based SSM shows the structure some better:

On 0:00 the percussion starts playing together with some synthesized pitches.
On 0:19 the synthesized pitches create sort of a melody.
On 0:37 this melody partly fades away and the percussion becomes more prominent.
On 0:57 the percussion seems to change somewhat.
From 1:04 on, the music starts having more sweeps and pitched elements. It starts sounding fuller. Each sweep or new element might be shown by a bright green line (many follow each other after around 80 seconds).

All these moments are shown by changes in the SSM. Even though there are more changes visible than I can hear in the music, it does a well job in showing the structure of the music.

Roemer_2

Chromagram and Cepstrogram

Chromagram

Cepstrogram

Self-similarity Matrices

Chroma-based Matrix

Timbre-based Matrix

Comments

The Chroma-based SSM shows a clear structure in the song. It looks very similar to the Timbre-based SSM and can be seen as A1-B-A2-Outro.

I will mainly use the Timbre-based SSM to set out a structure for the piece:

On 0:00 a guitar riff and percussion starts playing.
On 0:30 a sweep brings in a new synthesized melodic line and more percussion that plays along with the riff.
On 0:53 a the riff and synthesized melodic line disappear and get replaced by percussion.
On 1:01 long synthesized notes start playing over the percussion.
On 1:40 a new drum riff is added, which is marked by a clear line in the Chroma-based SSM.
On 1:50 the Chroma-based SSM shows a big changes (a wide green line), which indicates a modulation from D to C (as can be seen in the chromagram).

All these moments are shown by changes in the SSMs.

Keygrams & Chordograms

Keygrams

Keygrams: Marit_1

Ke_2

Sven_2

Sven_1

Roemer_1

Roemer_2

Chordograms

Chordograms: Marit_1

Ke_2

Sven_2

Sven_1

Roemer_1

Roemer_2

Comments

Comments: Marit_1

In this keygram, it is hard to find out which line really stand outs, since none of them is particularly dark. The lines of E major, B major, A major, A minor and E minor seem to be the darkest and, thus, the most prominent. E minor is the parallel minor key of E major and A minor is the parallel minor key of A major. It is likely that the music is either centered around A or E for this reason, rather than around B, since the line of B minor does not stand out much. Looking at the chromagram made before, the pitch classes E, F#, A and B seem to be the most recurring throughout the piece. G# seems to be constant throughout the piece as well, while C# and C alternate. At some parts there is also high energy in the pitch classes D and G. Although it is not very clear, I will suggest this piece uses a mixture of the A major and the three A minor scales (natural, harmonic and melodic).

Looking at the chordogram of Marit_1, the chord progression seems to show some ambiguity as well. The darkest lines correspond to the A minor and E minor chords throughout the whole song. However, such emphasis seems to be given to thr A major and E major chords. It might be possible, that the track uses power chords, rather than major or minor chords, which could justify the chordograms ambiguity between the major and minor variants of both chords and the keys. Besides this, B minor, B major, F# minor and D major chords are identified by the chordogram. The only chord that is less likely part of the A major or A minor key is B major, but this chord can be understood as the B minor chord or a power chord in most cases, since the chord has two notes in common with those chords and is to some extent similar.

Lastly, looking back at the most represented notes in the chordogram (E, F#, A and B) discussed before, the use of power chords can be set out more specifically. Often, the most important chords of a song are the tonic, subdominant / super tonic and dominant. In this song, assuming it is in A major or A melodic minor for most part, the power chords of the tonic (A-E), super tonic (B-F#) and dominant (E-B) can all be formed with the most represented notes in the chordogram.

Ke_2

In this keygram, it is hard to find out which line really stand outs, since none of them is particularly dark. The lines of Gb major, Db major, Ab major and Eb major seem to be the darkest and, thus, the most prominent. However, B major shows a few dark sections as well. B major is enharmonically equivalent to Cb major, which shows that the five darkest lines are all directly related to each other by the circle of fifths. The chromogram shows that the pitch classes B, C#, D#, E, F#, G# and A# are most important to the track. These pitches together form the B major scale. Interestingly enough, this is not the most clearly visible line in the keygram.

Looking at the chordogram of Ke_2, the chord progression seems to show some ambiguity as well. The darkest lines correspond to the G# minor, E major, C# minor and Gb major (enharmonically equivalent to F# major) chords throughout the whole song. Besides these chords, E minor and G# major have some darker parts in their line, which can be explained by the notes they share with their major variants, which are prominent in the track. Interestingly B major does not seem to be especially significant in the track, even though it is the tonic of the scale. This absence of very clear tonic statements could justify why the B major scale is not shown as a dark line in the keygram, even though it seems to be the best fit for the track.

Sven_2

In the prompts I asked the AI music generators to compose a piece in D major. Other than Sven_1, Sven_2 does not seem to be in D major. The D major line is light and instead the lines of C major and A major seem to be the darkest and, thus, the most prominent. However, another line that is remarkable is that of A minor, which is not the darkest, but it is on the darker side throughout the whole track. Between 50-100s more importance seems to be given to C major and between 110-160s this seems to shift to A major. A minor can in this sense be seen as the bridge between both scales: C major is its relative major key and A major is its parallel major key. Although the track is not in D major, the other three scales seem to work together (through modulation) to create the tonal space in this track.

Looking at the chordogram of Sven_2, the chord progression seems to show modulations as well. 0-50s puts the most emphasis on the A minor chord. A major and A7 is also apparent, likely because of the centricity of the tone A. 50-110s shows a shift to the C major, C minor, F minor chords (perhaps then not a shift to the key of C major, but to the key of C minor?), in which the A major line suddenly gets very bright compared to the former section (the chord is unlikely to appear in this section). 110-130s shows a shift again, emphasizing the chords of A major , A minor, F minor and D minor - a seemingly combination of the A major and A minor key. After 130s, the F minor chord disappears again, which puts a bigger emphasis on the A minor and D minor chords. With these chords, the track seems to end in the A minor key.

Sven_1

In the prompts I asked the AI music generators to compose a piece in D major. Looking at the keygram of Sven_1, the darkest lines correspond to the keys of D major, D minor and A major. D minor is the parallel minor of D major. Because of the centricity of the tone D within both scales, it is not odd that D minor seems prominent in the keygram. The prominence of A major can also be explained, because of its neighboring position to D major in the circle of fifths. The two keys have six corresponding notes and the tone A (as well as the A major chord) has an important function as dominant in the scale of D major.

Looking at the chordogram of Sven_1, the darkest spots appear at the following chords: D major, A major, G major, B minor and F# minor. These are the tonic, dominant, subdominant, submediant and mediant of the D major scale respectively. The chords are, thus, all diatonic chords and their appearance in the piece are not surprising. Two other remarkable lines are those of D minor and G minor. These two chords appear in the D minor scale, which explains - together with the understanding that this is the parallel minor of D major - why they appear in the chordogram as well.

Roemer_1

In this keygram, it is hard to find out which line really stand outs, since none of them is particularly dark. The lines of A major and A minor seem to have the darkest parts. Relating this to the chromagram, the pitch class A indeed seems to be the most prominent. However, all other pitch classes seem to be present in the track as well, favoring pitch classes E and F the most besides A.

Looking at the chordogram of Roemer_1, the chord progression seems unclear as well. All lines have some dark spots and some light spots, which makes it hard to distinguish which one is actually important to the track. The D minor and F major chords seem to have the darkest spots on the line and might be the darkest two lines throughout the whole track

The failure of the keygram and chordogram to clearly identify the key and chord progressions in the track, could to some extent be explained by what is audible. The track exists mainly out of percussion. The synthesized sounds shift a lot and have many effects on them, making it hard to discern a clear pitch and thus a specific key and chords.

Roemer_2

For most of this keygram, the darkest lines correspond to the D major and D minor keys. D minor is the relative minor key of D major, which they are similar in pitch center and share many notes. This accounts for the prominence of both of the keys together. From around 115 seconds until the end of the song, the keygram shows dark lines at the C major and C minor keys. This indicates a downwards modulation of two semitones. From 55-70 seconds, the keygram does not clearly indicate a key, there seems to be a vaguely, yet quickly ascending pattern.

Looking at the chordogram of Roemer_2, the chord progression seems to show modulations as well. Most of the chordogram shows dark lines at the chords G major, G minor, B major, B minor, D major and D minor. Since all lines are equally dark, it is not really possible to indicate which of the chords is most important. However, all of the chords include the pitch class D, which again reinforces the importance of this pitch class to the track. From 115 onward, it can be seen that, aside from the key, also the chords shift to favor the pitch class C. The period between 55-70 seconds, the chordogram also does not favor any specific chords.

The structure of the keygram and chordogram is very similar to that of the Self-Similarity Matrices and can be explained by what is audible in the track. The parts that center the pitch class D both contain a riff that mostly plays this tone. The part between 55-70 second mostly consists of percussion without any identifiable pitches. Lastly, the ending of the song modulates the riff on D two semitones downwards to C.

Marit_1

Novelty functions

Energy-based novelty function

Spectral novelty function

Tempograms

Tempogram

Cyclic Tempogram

Comments

The tempogram of Marit_1 shows very clear lines around 125 BMP, 250 BPM, 375 BPM and 500 BPM. Besides this, a small part of the line at 625 BPM can be perceived. The cyclic tempogram shows a very clear line around 125 BPM. Besides this, there are two somewhat vaguer lines around 155 BPM and 95 BPM. If I tap along with the music, I tap around 126 BPM, so that would be an accurate estimate. In that case, 250 BPM, 375 BPM, 500 BPM and 625 BPM would be tempo upper harmonics.

In the high-level corpus features, the tempo of this track is presented as 126 BPM, which is very accurate.

In order to understand the lines around 95 BPM and 155 BPM in the cyclic tempogram, I will take a look at the ratios described in the JUST intonation. The tempogram shows five of the tempo harmonics, which can be compared to the first five pitch harmonics in the overtone series: C2-C3-G3-C4-E4. Ratios that can be derived from these harmonics are:

These are the only possible types of tempo intervals in this situation, since other ratios cannot be made with the given harmonics.

When relating the lowest line in the cyclic tempogram around 95 BPM to the tempo of the track, gives the ratio: 126/95 = 1.32631579. This is very close to the outcome of the 4/3 ratio, which justifies to call 95 BPM the tempo subdominant.

Now relating the highest line in the cyclic tempogram around 155 BPM to the tempo of the track, gives the ratio: 155/126 = 1.23015873. This is very close to the outcome of the 5/4 ratio, which justifies to call 155 BPM the tempo mediant.

Lastly the dip in tempo shown in the cyclic tempogram could be seen as deriving from the upper harmonics, since the line around 126 BPM only shows a small dip and the upper harmonics show greater dips each next harmonic. The small dip could be explained by the difference in the structure of the music that happens around the same time.

Ke_2

Novelty functions

Energy-based novelty function

Spectral novelty function

Tempograms

Tempogram

Cyclic Tempogram

Comments

The tempogram of Ke_2 shows very clear lines around 95 BMP, 190 BPM, 285 BPM, 380 BPM, 475 BPM and 570 BPM. The cyclic tempogram shows a very clear line around 95 BPM. Besides this, there are two somewhat vaguer lines around 120 BPM and 143 BPM. If I tap along with the music, I tap around 95 BPM, so that would be an accurate estimate. In that case, 190 BPM, 285 BPM, 380 BPM, 475 BPM and 570 BPM would be tempo upper harmonics.

In the high-level corpus features, the tempo of this track is presented as 95 BPM, which is very accurate.

In order to understand the lines around 120 BPM and 143 BPM in the cyclic tempogram, I will take a look at the ratios described in the JUST intonation. The tempogram shows six of the tempo harmonics, which can be compared to the first six pitch harmonics in the overtone series: C2-C3-G3-C4-E4-G4. Ratios that can be derived from these harmonics are:

These are the only possible types of tempo intervals in this situation, since other ratios cannot be made with the given harmonics.

When relating the middle line in the cyclic tempogram around 120 BPM to the tempo of the track, gives the ratio: 120/95 = 1.26315789. This is very close to the outcome of the 5/4 ratio, which justifies to call 120 BPM the tempo mediant.

Now relating the highest line in the cyclic tempogram around 143 BPM to the tempo of the track, gives the ratio: 143/95 = 1.50526316. This is very close to the outcome of the 3/2 ratio, which justifies to call 143 BPM the tempo dominant.

Sven_2

Novelty functions

Energy-based novelty function

Spectral novelty function

Tempograms

Tempogram

Cyclic Tempogram

Comments

The tempogram of Sven_2 shows very clear lines around 180 BMP, 360 BPM and 540 BPM. The cyclic tempogram shows a very clear line around 90 BPM. Besides this, there is a somewhat vaguer line around 135 BPM. If I tap along with the music, I tap around 90 BPM, so that would be an accurate estimate. In that case, 180 BPM, 360 BPM and 540 BPM would be tempo upper harmonics.

In the high-level corpus features, the tempo of this track is presented as 90 BPM, which is very accurate.

In order to understand the line around 135 BPM in the cyclic tempogram, I will take a look at the ratios described in the JUST intonation. The tempogram shows three of the tempo harmonics, which can be compared to the first three pitch harmonics in the overtone series: C2-C3-G3. Ratios that can be derived from these harmonics are:

1 / 1 = 1 (prime)
3 / 2 = 1.5 (dominant)
2 / 1 = 2 (octave)

These are the only possible types of tempo intervals in this situation, since other ratios cannot be made with the given harmonics.

When relating the upper line in the cyclic tempogram around 135 BPM to the tempo of the track, gives the ratio: 135/90 = 1.5. This is equal to the outcome of the 3/2 ratio, which justifies to call 135 BPM the tempo dominant.

Lastly the dip in tempo shown in the cyclic tempogram could be seen as deriving from the upper harmonics, since the line around 180 BPM only shows a small dip and the upper harmonics show greater dips with each next harmonic. The small dip could be explained by the difference in the structure of the music that happens around the same time.

Sven_1

Novelty functions

Energy-based novelty function

Spectral novelty function

Tempograms

Tempogram

Cyclic Tempogram

Comments

The tempogram of Sven_1 shows very clear lines around 160 BMP, 320 BPM and 480 BPM. The cyclic tempogram shows very clear lines around 80 BPM and 160 BPM. Besides this, there is a somewhat vaguer line around 120 BPM. If I tap along with the music, I tap around 160 BPM, so that would be an accurate estimate. In that case, 330 BPM and 500 BPM would be tempo upper harmonics and 80 BPM would be a tempo subharmonic. 120 BPM could be seen as a tempo lower fourth in relation to 160 BPM.

In the high-level corpus features, the tempo of this track is presented as 81 BPM, which is accurate. I tapped along at 160 BPM, but 81 BPM (as it’s lower octave) makes sense as well.

In order to understand the lines around 80 BPM and 120 BPM in the cyclic tempogram, I will take a look at the ratios described in the JUST intonation. The tempogram shows three of the tempo harmonics, which can be compared to the first three pitch harmonics in the overtone series: C2-C3-G3. Ratios that can be derived from these harmonics are:

1 / 1 = 1 (prime)
3 / 2 = 1.5 (dominant)
2 / 1 = 2 (octave)

These are the only possible types of tempo intervals in this situation, since other ratios cannot be made with the given harmonics.

When relating the middle line in the cyclic tempogram around 120 BPM to the tempo of the track, gives the ratio: 120/80 = 1.5. This is equal to the outcome of the 3/2 ratio, which justifies to call 120 BPM the tempo dominant.

Now relating the lowest line in the cyclic tempogram around 80 BPM to the tempo of the track, gives the ratio: 160/80 = 2. This is equal to the outcome of the 2/1 ratio, which justifies to call 80 BPM the (lower) tempo octave.

Lastly the tempo shown in the (cyclic) tempogram does not seem to be very steady. There is a lot of fluctuation, which seems to partly coincide with changes in the musical structure. At some places, for example around 60 seconds, the tempogram has vertical lines, which shows that the tempo at such places is hard to define. At such places, there is some more silence in the track, which gives uncertainty in where to identify the beat.

Roemer_1

Novelty functions

Energy-based novelty function

Spectral novelty function

Tempograms

Tempogram

Cyclic Tempogram

Comments

The tempogram of Roemer_1 shows very clear lines around 100 BMP, 200 BPM, 300 BPM, 400 BPM, 500 BPM and 600 BPM. The cyclic tempogram shows a very clear line around 100 BPM. Besides this, there are two somewhat vaguer lines around 125 BPM and 150 BPM. If I tap along with the music, I tap around 100 BPM, so that would be an accurate estimate. In that case, 200 BPM, 300 BPM, 400 BPM, 500 BPM and 600 BPM would be tempo upper harmonics.

In the high-level corpus features, the tempo of this track is presented as 99 BPM, which is pretty accurate.

In order to understand the lines around 125 BPM and 150 BPM in the cyclic tempogram, I will take a look at the ratios described in the JUST intonation. The tempogram shows six of the tempo harmonics, which can be compared to the first six pitch harmonics in the overtone series: C2-C3-G3-C4-E4-G4. Ratios that can be derived from these harmonics are:

These are the only possible types of tempo intervals in this situation, since other ratios cannot be made with the given harmonics.

When relating the middle line in the cyclic tempogram around 125 BPM to the tempo of the track, gives the ratio: 125/100 = 1.25. This is equal to the outcome of the 5/4 ratio, which justifies to call 125 BPM the tempo mediant.

Now relating the highest line in the cyclic tempogram around 150 BPM to the tempo of the track, gives the ratio: 150/100 = 1.5. This is equal to the outcome of the 3/2 ratio, which justifies to call 150 BPM the tempo dominant.

Lastly, there are vague lines surrounding each line in the (cyclic) tempogram. The percussion in the track is very audible, which might excite high tempo harmonics (> 600 BPM), so that they appear in the tempogram. Even though these tempo harmonics might only be shown at a higher BPM in the tempogram, they are vaguely apparent already in this part of it.

Roemer_2

Novelty functions

Energy-based novelty function

Spectral novelty function

Tempograms

Tempogram

Cyclic Tempogram

Comments

The tempogram of Roemer_2 shows very clear lines around 120 BMP, 240 BPM, 360 BPM and 480 BPM. Besides this, the line which would appear around 600 BPM (being the upper limit of the graph) is not yet fully visible. The cyclic tempogram shows a very clear line around 120 BPM. Besides this, there are two somewhat vaguer lines around 93 BPM and 155 BPM. If I tap along with the music, I tap around 123 BPM, so that would be an accurate estimate. In that case, 240 BPM, 360 BPM and 480 BPM would be tempo upper harmonics.

In the high-level corpus features, the tempo of this track is presented as 63 BPM, which is accurate. I tapped along at 123 BPM, but 63 BPM (as it’s lower octave) makes sense as well.

In order to understand the lines around 93 BPM and 165 BPM in the cyclic tempogram, I will take a look at the ratios described in the JUST intonation. The tempogram shows five of the tempo harmonics, which can be compared to the first five pitch harmonics in the overtone series: C2-C3-G3-C4-E4. Ratios that can be derived from these harmonics are:

These are the only possible types of tempo intervals in this situation, since other ratios cannot be made with the given harmonics.

When relating the lowest line in the cyclic tempogram around 93 BPM to the tempo of the track, gives the ratio: 123/93 = 1.32258065. This is very close to the outcome of the 4/3 ratio, which justifies to call 93 BPM the tempo subdominant.

Now relating the highest line in the cyclic tempogram around 155 BPM to the tempo of the track, gives the ratio: 155/123 = 1.2601626. This is very close to the outcome of the 5/4 ratio, which justifies to call 155 BPM the tempo mediant.

Lastly, there are vague vertical lines around 60-70 seconds in the (cyclic) tempogram. In this small section, the high-hat stops and is not yet replaced by some another musical element that indicates each beat. The lines can thus be related to musical structure (the same section is highlighted in the Self-Similarity Matrices). The (cyclic) tempogram is still able to identify the tempo, but the vertical lines surrounding the section show some kind of ambiguity.

Clustering and Heatmap

Hierarchical clustering

Heatmap

Comments

Comments: Hierarchical Clustering

This graph shows which tracks are clustered togehter based on the Essentia-features. To create a slightly bigger graph, I added six songs, instead of only using the six I have been working with so far. What is shown are the three tracks with the lowest danceability score, the three tracks with the highest danceability score, my own tracks and two tracks that surround each of my own tracks. This visualisation shows that tracks that would be clustered together based only on danceability are not necessarily as close together when taking all different features into account.

Heatmap

This heatmap shows how the tracks relate to each other based on the Essentia-features. To create a slightly bigger graph, I added six songs, instead of only using the six I have been working with so far. What is shown are the three tracks with the lowest danceability score, the three tracks with the highest danceability score, my own tracks and two tracks that surround each of my own tracks. This visualisation shows what features are the basis for clustering the tracks together and how the features can be clustered together.

Knn Classification

Graphs

Mosaic Matrix

Heatmap Matrix

Tables and comments

Knn Classification

               Truth
Prediction      Danceable Not-Danceable
  Danceable            11            15
  Not-Danceable        11            53

Precision and Recall

# A tibble: 2 × 3
  class         precision recall
  <fct>             <dbl>  <dbl>
1 Danceable         0.423  0.5  
2 Not-Danceable     0.828  0.779

Comments

These matrices show how well the model works. It can be seen that there are 9 True Positives, 15 False Positives, 13 False Negatives and 53 True Negatives. The model has an accuracy of 68.9%. There are not many songs that are labeled as danceable, which causes the model to have lower precision and recall scores on this class. Because it has many examples of non-danceable songs, it is easier to identify this class in a training set.

Decision-tree Classification

Variable importance

Variable Importance

Heatmap Matrix

Further information

Precision and Recall

# A tibble: 2 × 3
  class         precision recall
  <fct>             <dbl>  <dbl>
1 Danceable         0.364  0.182
2 Not-Danceable     0.772  0.897

Comments

It can be seen that arousal is the most influential on the model’s prediction whether a track is made by AI or not. Besides this, matrix shows that there are 3 True Positives, 9 False Positives, 19 False Negatives and 59 True Negatives. The model has an accuracy of 68.9%. There are not many songs that are labeled as danceable, which causes the model to have lower precision and recall scores on this class. Because it has many examples of non-danceable songs, it is easier to identify this class in a training set.

Final Plot

Final plot

Variables which are of great importance for predicting danceability

Comments

This plot shows the relation of arousal, engagingness and approachability to danceability. These three features turned out to be most important for the model to decide whether a song is danceable or not. Interestingly, in this graph danceable songs are spread through the non-danceable songs. There does not seem to be a very clear seperation of both based on these features.

Conclusion

To end this dashboard, I will give a short conclusion and summary of what is shown throughout the pages.

Class Corpus Table This table shows all the tracks present in the class corpus and their corresponding Essentia-features. I modified the table slightly (I added name, dance and ai_int) for later parts of my analysis.

First Class Corpus Visualisations: Here I have shown a few visualisations that introduce the topic of my dashboard: danceability! I showed a few features which I thought were closely related to danceability, all tracks in the class corpus ordered by their danceability and the selection of tracks that I have analyzed throughout this dashboard.

Self-Similarity Matrices based on Chromagrams and Cepstrograms In this section, I have shown Chromagrams, Cepstrograms and Self-Similarity Matrices of the six tracks. I have analysed the tracks based on their structure, which was easier for some of them than for others. I expected tracks with a clear structure to be the most danceable. However, the least danceable ones were pretty structured, especially Ke_2. Contrasting Roemer_1 did not seem very structured, but is still very danceable. Of my own tracks, Sven_1 is not really structured and Sven_2 has a slightly clearer structure. It does not seem like structure is closely related to danceability.

Keygrams and Chordograms In this section, I have shown Keygrams and Chordograms of the six tracks. I have analysed the songs based on their tonal features and did not expect a clear tonal basis to be very relevant to danceability. This seems to be true, since some of the least danceable tracks show a clear tonal basis (for example Sven_1), but some also show a less clear tonal basis (for example Marit_1). The same thing could be said about the danceable tracks, since Roemer_1 does not have a clear tonal basis and Roemer_2 has a somewhat clearer tonal basis.

Novelty Functions and Tempograms In this section, I have shown Novelty Functions and Tempograms of the six tracks. I have analysed the song based on their tempo and expected a tempo around 125 BPM to be the most danceable. This does not seem to be true, since Marit_1 is the least danceable track, but has a tempo of 126 BPM. Although the most danceable track (Roemer_2) has a BPM of 123 BPM, the second most danceable track (Roemer_1) has a BPM of 100. My own tracks (Sven_1 and Sven_2) have very different BPMs of 160 and 95 respectively.

Clustering and Classification In this section, I have shown Hierarchical Clustering and a Heatmap in relation to twelve tracks out of the class corpus. Interestingly, my own tracks are clustered together on the lowest level. Even though they sound very distinct to me, the prompts I used to create them did apparently make the tracks similar somehow. None of the other six tracks I have analysed are clustered together on the lowest level. Looking at the heatmap, the valance and instrumentalness of my own tracks are almost the same.

Besides this, I have created models to predict whether a track is danceable or not in this section. Although the models did well on finding true negatives, true positives tended to be harder to find. This might be, because the class corpus contained only a little amount of danceable tracks (danceability >= 0.7) compared to non-danceable tracks.

Lastly, the decision-tree model showed which features are most important to decide whether a track is danceable or not. The three most important features (arousal, approachability and engagingness) were then used to create the final plot of this dashboard, in which these features are related to the danceability of each track.

Thank you for taking the time to visit and read my dashboard :)